The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Kingdom of Eswatini: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49). Methodology These high-resolution maps are created using machine learning techniques to identify buildings from commercially available satellite images. This is then overlayed with general population estimates based on publicly available census data and other population statistics at Columbia University. The resulting maps are the most detailed and actionable tools available for aid and research organizations. For more information about the methodology used to create our high resolution population density maps and the demographic distributions, click here. For information about how to use HDX to access these datasets, please visit: https://dataforgood.fb.com/docs/high-resolution-population-density-maps-demographic-estimates-documentation/ Adjustments to match the census population with the UN estimates are applied at the national level. The UN estimate for a given country (or state/territory) is divided by the total census estimate of population for the given country. The resulting adjustment factor is multiplied by each administrative unit census value for the target year. This preserves the relative population totals across administrative units while matching the UN total. More information can be found here

Abstract

The 2006-07 Swaziland Demographic and Health Survey (SDHS) is a nationally representative survey of 4,843 households, 4,987 women age 15-49, and 4,156 men age 15-49. The SDHS also included individual interviews with boys and girls age 12-14 and older adults age 50 and over. The survey of persons age 12-14 and age 50 and over was carried out in every other household selected in the SDHS. Interviews were completed for 459 girls and 411 boys age 12-14, and 661 women and 456 men age 50 and over.

The 2006-07 SDHS is the first national survey conducted in Swaziland as part of the Demographic and Health Surveys (DHS) programme. The data are intended to furnish programme managers and policymakers with detailed information on levels and trends in fertility; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of mothers and young children; early childhood mortality and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The survey also collected information on malaria prevention and treatment.

The 2006-07 SDHS is the first nationwide survey in Swaziland to provide population-based prevalence estimates for anaemia and HIV. Children age 6 months and older as well as adults were tested for anaemia. Children age 2 years and older as well as adults were tested for HIV.

The principal objective of the 2006-07 Swaziland Demographic and Health Survey (SDHS) was to provide up-to-date information on fertility, childhood mortality, marriage, fertility preferences, awareness, and use of family planning methods, infant feeding practices, maternal and child health, maternal mortality, HIV/AIDS-related knowledge and behaviour and prevalence of HIV and anaemia.

More specifically the 2006-07 SDHS was aimed at achieving the following; - Determine key demographic rates, particularly fertility, under-five mortality, and adult mortality rates - Investigate the direct and indirect factors which determine the level and trends of fertility - Measure the level of contraceptive knowledge and practice of women and men by method - Determine immunization coverage and prevalence and treatment of diarrhoea and acute respiratory diseases among children under five - Determine infant and young child feeding practices and assess the nutritional status of children 6-59 months, women age 15-49 years, and men aged 15-49 years - Estimate prevalence of anaemia - Assess knowledge and attitudes of women and men regarding sexually transmitted infections and HIV/AIDS, and evaluate patterns of recent behaviour regarding condom use - Identify behaviours that protect or predispose the population to HIV infection - Examine social, economic, and cultural determinants of HIV
- Determine the proportion of households with orphans and vulnerable children (OVCs) - Determine the proportion of households with sick people taken care at household level - Determine HIV prevalence among males and females age 2 years and older - Determine the use of iodized salt in households - Describe care and protection of children age 12-14 years, and their knowledge and attitudes about sex and HIV/AIDS.

This information is intended to provide data to assist policymakers and programme implementers to monitor and evaluate existing programmes and to design new strategies for demographic, social and health policies in Swaziland. The survey also provides data to monitor the country's achievement towards the Millenium Development Goals.

MAIN RESULTS

• Fertility in Swaziland has been declining rapidly, with the TFR falling from 6.4 births per woman in 1986 to 3.8 births at the time of the SDHS. As expected, fertility is higher in rural areas (4.2 births per woman) than in urban areas (3.0 births per woman). Fertility differentials by education and wealth are substantial. Women with no education have on average 4.9 children compared with 2.4 children for women with tertiary education. Fertility varies widely according to household wealth. Women in the highest wealth quintile have 2.9 children fewer than women in the lowest quintile (2.6 and 5.5 births per woman, respectively).

• Knowledge of family planning is universal in Swaziland. The most widely known method is the male condom (99 percent for both males and females). Among women, other widely known methods include injectables (96 percent), the pill (95 percent), and the female condom (91 percent). For men, the best known methods besides the male condom are the female condom (94 percent) and the pill and injectables (84 percent each).

• Children are considered fully vaccinated when they receive one dose of BCG vaccine, three doses each of DPT and polio vaccines, and one dose of measles vaccine. BCG coverage among children age 12-23 months is nearly universal (97 percent); coverage is also high for the first doses of DPT (96 percent) and polio (97 percent). The proportion of children receiving subsequent doses of DPT and polio vaccines drops slightly, with 92 percent of children receiving the third dose of DPT and 87 percent receiving the third dose of polio. Ninety-two percent of children had received a measles vaccination by the time of the SDHS. Overall, 82 percent of children age 12-23 months are fully immunised.

• In Swaziland, almost all women who had a live birth in the five years preceding the survey received antenatal care from health professionals (97 percent); 9 percent received care from a doctor, and 88 percent received care from a trained nurse or midwife. Only 3 percent of mothers did not receive any antenatal care

• Overall, 87 percent of children in Swaziland are breastfed for some period of time (ever breastfed). The median duration of any breast-feeding in Swaziland is almost 17 months. However, the median duration of exclusive breast-feeding is much shorter (0.7 months).

• In interpreting the malaria programme indicators in Swaziland, it is important to recognise that the disease affects an estimated 30 percent of the population where malaria is most prevalent (the Lubombo Plateau, the lowveld, and parts of the middleveld). Malaria is also seasonal, occurring mainly during or after the rainy season (from November to March). A substantial part of the SDHS fieldwork took place outside of this period.

• Results from the HIV testing component in the 2006-07 SDHS indicate that 26 percent of Swazi adults age 15-49 are infected with HIV. Among women, the HIV rate is 31 percent, compared with 20 percent among men. HIV prevalence peaks at 49 percent for women age 25-29, which is almost five times the rate among women age 15-19 and more than twice the rate observed among women age 45-49. HIV prevalence increases from 2 percent among men in the 15-19 age group to 45 percent in the age group 35-39 and then decreases to 28 percent among men age 45-49. HIV prevalence for women and men age 50 or over is 12 percent and 18 percent, respectively. Among the population age 2-14 years, 4 percent of girls and boys are infected.

Geographic coverage

The 2006-07 Swaziland Demographic and Health Survey (SDHS) is a nationally representative survey. It was designed to provide estimates of health and demographic indicators at the national level, for urban-rural areas, and for the four regions of Manzini, Hhohho, Lubombo, and Shiselweni.

Analysis unit

• Household
• Women age 15-49
• Men age 15-49
• Young adults age 12-14
• adults age 50 and over

Universe

The population covered by the 2006 SWZDHS is defined as the universe of all women Ever-married women in the reproductive ages (i.e., women 15-49).

Kind of data

Sample survey data

Sampling procedure

The 2006-07 SDHS was designed to provide estimates of health and demographic indicators at the national level, for urban-rural areas, and for the four regions of Manzini, Hhohho, Lubombo, and Shiselweni. Standard DHS sampling policy recommends a minimum of 1,000 to 1,200 women per major domain. To meet this criterion, the number of households selected in each of the various domains, particularly urban areas, was not proportional to the actual size of the population in the domain. As a result, the SDHS sample is not self-weighting at the national level, and weights must be applied to the data to obtain the national-level estimates.

The 2006-07 SDHS sample points (clusters) were selected from a list of enumeration areas (EAs) defined in the 1997 Swaziland Population and Housing Census. A total of 275 clusters were drawn from the census sample frame, 111 in the urban areas and 164 in the rural areas.

CSO staff conducted an exhaustive listing of households in each of the SDHS clusters in August and September 2005. From these lists, a systematic sample of households was drawn for a total of 5,500 households. All women and men age 15-49 identified in these households were eligible for individual interview. In addition, a sub-sample of half of these households (2,750 households) was selected randomly in which all boys and girls age 12-14 and persons age 50 and older were eligible for individual interview. In the SDHS households where youth and older adults were interviewed, all individuals age 6 months and older were eligible for anaemia testing and all individuals age 2 and older were eligible for HIV testing. In the SDHS households where only women and men age 15-49 were interviewed, children age 6 months to 5 years were eligible for the anaemia testing and women and men age 15-49 were eligible for anaemia and HIV testing.

During the household listing, field staff used Global Positioning System (GPS) receivers to establish and record the

Constrained estimates of total number of people per grid square broken down by gender and age groupings (including 0-1 and by 5-year up to 90+) for Eswatini, version v1. The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The units are estimated number of male, female or both in each age group per grid square.

More information can be found in the Release Statement

The difference between constrained and unconstrained is explained on this page: https://www.worldpop.org/methods/top_down_constrained_vs_unconstrained

File Descriptions:

{iso} {gender} {age group} {year} {type} {resolution}.tif

iso

Three-letter country code

gender

m = male, f= female, t = both genders

age group

• 00 = age group 0 to 12 months
• 01 = age group 1 to 4 years
• 05 = age group 5 to 9 years
• 90 = age 90 years and over

year

Year that the population represents

type

CN = Constrained , UC= Unconstrained

resolution

Resolution of the data e.q. 100m = 3 arc (approximately 100m at the equator)

Abstract

The Kingdom of Eswatini Multiple Indicator Cluster Survey (MICS5) 2014 was conducted in 2014 by the Central Statistical Office with technical and financial support from UNICEF. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Among these global commitments are those emanating from the World Fit for Children Declaration and Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium Development Goals (MDGs).

The 2014 Kingdom of Eswatini MICS5 has as its primary objectives to:

• Provide up-to-date information on the situation of women, children, men and other vulnerable populations in Kingdom of Eswatini;

• Generate data for the critical assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention;

• Furnish data needed for monitoring progress toward goals established in the Millennium Declaration and other internationally agreed upon goals, as a basis for future action;

• Collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable;

• Contribute to the generation of baseline data for the post-2015 agenda;

• Validate data from other sources and the results of focused interventions.

• Track progress made in the implementation of national commitments, strategies and frameworks, National Development Strategy (NDS) Vision 2022, PRSAP 2008, extended National Strategic Framework 2014-2018, National Health Sector Strategic Plan (NHSSPII), and National Plan of Action for Children 2011-2015. · Identify new areas of concern for government and partners.

Geographic coverage

The 2014 Kingdom of Eswatini MICS was designed to provide estimates for indicators on the situation of the country at the national level, for urban and rural areas, and for the four administrative regions of Kingdom of Eswatini: Hhohho, Manzini, Shiselweni and Lubombo.

Analysis unit

• Individuals

• Households

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years, all men age 15-49 years and all children under 5 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design features include target sample size, sample allocation, sampling frame and listing, choice of domains, sampling stages, stratification, and the calculation of sample weights.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

The sample size required based on the desired level of precision for the Kingdom of Eswatini MICS was calculated as 5,205 households. For calculating this sample size, the key indicator used was the prevalence of pneumonia among children age 0-59 months, estimated to be 0.13 from the 2010 MICS.

The number of households selected per cluster for the 2014 Kingdom of Eswatini MICS5 was determined as 15 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 347 sample clusters would need to be selected nationwide.

SAMPLING FRAME AND SELECTION OF CLUSTERS

The 2007 census frame was used for the selection of clusters. Census enumeration areas were defined as primary sampling units (PSUs), and were selected from each of the sampling strata by using systematic pps (probability proportional to size) sampling procedures, based on the number of households in each enumeration area from the 2007 Population and Housing Census frame. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the four regions, separately for the urban and rural strata.

LISTING ACTIVITIES

The sampling frame (the 2007 population census) was not up-to-date, so the more recent listing of households conducted for the ILFS 2013/14 was used for the selection of the 5,211 households from the 347 sample clusters for the MICS in order to reduce the total survey costs, as described above. Therefore, a separate new listing of households was not conducted for the MICS.

SELECTION OF HOUSEHOLDS

The list of households from the ILFS 2013/14 for each of the 347 sample EAs was used for selecting the sample households for MICS. The households were sequentially numbered from 1 to N (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 15 households in each enumeration area was carried out using random systematic selection procedures. The survey also had a questionnaire for men that was administered in every third household in each sampled cluster for interviews with all eligible men.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a questionnaire for individual women administered in each household to all women age 15-49 years; 3) a questionnaire for individual men administered in every three households to all men age 15-59 years; and 4) an under-five questionnaire, administered to mothers (or caretakers) of all children under-five years of age living in the household.

The questionnaires are based on the MICS5 model questionnaires. From the MICS5 model English, version, the questionnaires were customised and translated into siSwati and were pre-tested in Moti, Sphocosini and the Police College in July 2014. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Kingdom of Eswatini MICS5 questionnaires is provided as a Related Material.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, and measured the weights and heights of children age under-five years. Details and findings of these observations and measurements are provided in the respective sections of the report

A number of country specific modifications were also made to better serve the data needs of the country. The modifications include the following:

Modules that are not part of the generic MICS5 that have been included in the Kingdom of Eswatini 2014 MICS5:

Household Questionnaire

• Children Orphaned or made Vulnerable (children 0-17 years)

• Basic Needs (children age 5-17 years)

Questionnaire for Individual Women

• Non Communicable Diseases

• Social Participation

Questionnaire for Individual Men

• Non Communicable Diseases

• Social Participation

Modules that are part of the generic MICS5 that have been omitted:

Household Questionnaire

• Child Labour

• Insecticide Treated Nets

• Indoor Residual Spraying

Women Questionnaire

• Female Genital Cutting Under-Five Questionnaire

• Malaria

Cleaning operations

Data was entered using the CSPro software, Version 5.0. The data was entered on seven desktop computers and carried out by seven data entry operators and one data entry supervisor. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS programme and adapted to the Kingdom of Eswatini MICS5 questionnaire were used throughout. Data processing began simultaneously with data collection in August 2014 and was completed in November 2014. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose.

Response rate

Of the 5,205 households selected for the sample, 4,981 were found to be occupied. Of these, 4,865 were successfully interviewed for a household response rate of 98 percent.

In the interviewed households, 5,001 women (age 15-49 years) were identified. Of these, 4,762 were successfully interviewed, yielding a response rate of 95 percent within the interviewed households.

The survey also sampled men (age 15-59 years) but required only a subsample. All men (age 15-59 years) were identified in every third household. A total of 1,629 men (age 15-59 years) were listed in the household questionnaires. Questionnaires were completed for 1,459 eligible men, which corresponds to a response rate of 90 percent within eligible interviewed households.

There were 2,728 children under-five years listed in the household questionnaires. Questionnaires were completed for 2,693 of these children, which corresponds to a response rate of 99 percent within interviewed households.

Sampling error estimates

The sample of respondents selected for the Kingdom of EswatiniMultiple Indicator Cluster Survey is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known

Abstract

This report presents results of the 2010 the Kingdom of Eswatini MICS, carried out by CSO in collaboration with UNICEF and other partners. Since its launch in the mid-1990s, MICS has become one of the largest sources of information on a range of indicators including child health, nutrition, water and sanitation, reproductive health, education, child protection and HIV/AIDS. The 2010 Kingdom of Eswatini MICS was implemented to assess the current situation of the Swazi population, particularly children and women, as well as to measure progress towards goals and targets emanating from international agreements: the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000, and the WFFC Plan of Action, adopted by 189 Member States at the United Nations (UN) Special Session on Children in May 2002. Both of these commitments build upon promises made by the international community at the 1990 World Summit for Children.

The 2010 Kingdom of Eswatini MICS is based on a nationally representative sample of 5,475 households selected from 365 enumeration areas distributed in the four regions of the country. It is an important source of information for measuring progress towards targets set by these various strategic plans, as well international declarations including the MDGs, the United Nations General Assembly Special Session Declaration of Commitment on HIV/AIDS (UNGASS) and others commitments.

Geographic coverage

National

Analysis unit

• individuals
• households

Universe

The survey covered all de jure household members (usual residents), all women aged between 15-49 years, all children under 5 living in the household, and all men aged 15-59 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the 2010 Kingdom of Eswatini MICS was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the four regions of the country (Hhohho, Manzini, Shiselweni and Lubombo).

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The 2006/07 Swaziland Demographic Health Survey (SDHS) collected many of the indicators in the MICS. Therefore, the results of the 2006/07 SDHS and the sample design were used as a reference in finalizing the sample design for the 2010 Swaziland MICS. In the survey, most of the indicators will be tabulated at the national level, urban and rural domains, and for the four regions as in the case of the 2006/07 SDHS.

The sampling frame for MICS comes from the recent Kingdom of Eswatini Census of Population and Housing data collected in 2007. The primary sampling units (PSUs) are the census enumeration areas (EAs). The EAs were created for the 2007 Census operations with well-defined boundaries identified on sketch maps. The number of households in an EA is based on the expected workload for one enumerator. According to the 2007 Census, the average number of households per EA is 103 (274 for rural EAs and 34 for urban EAs).

The sample size for a good household survey, such as the 2010 Kingdom of Eswatini MICS, is determined by the accuracy required for the estimates for each domain, as well as by the resource and operational constraints. The allocation of the sample EAs in each region to the rural and urban strata will be proportional to the number of households. Based on these criteria, the proposed allocation of sample EAs and households by region and rural and urban stratum results in a total sample of 365 EAs and 5,475 households.

The sampling procedures are more fully described in "Swaziland Multiple Indicator Cluster Survey 2010 - Final Report" pp.A1-A6.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2010 Kingdom of Eswatini MICS consists of four main questionnaires including a household questionnaire, women’s and men’s questionnaires and a questionnaire for children under age five. The survey includes information on key indicators on the following topics:

Household questionnaire: age, sex, urban vs. rural residency, household composition, education of household members, household assets, water and sanitation, use of iodized salt, use of insecticidetreated nets (ITNs), orphanhood and vulnerability of children, child labor and child discipline.

Questionnaire for children under five: birth registration, early childhood development, infant and young child feeding, care of illness (including diarrhoea and pneumonia), malaria, immunization and anthropometry.

Women’s questionnaire: child mortality, birth history, desire for last birth, maternal an newborn health, illness symptoms, contraception, unmet need, marriage/union, sexual behaviour, HIV/AIDS, sexually transmitted infections (STIs), and attitudes towards domestic violence.

Men’s questionnaire: marriage/union, attitudes towards contraception, sexual behaviour, HIV/AIDS, STIs, male circumcision and attitudes towards domestic violence.

Cleaning operations

Data entry commenced on 3 September after an initial training and ended on 17 December 2010. Data were entered on 10 computers by 10 data entry operators and two data entry supervisors using the CSPro software. In order to ensure quality control, all questionnaires were double entered and two secondary editors complemented the efforts of entry supervisors to perform internal consistency checks. Procedures and standard programmes developed under the global MICS4 survey were adapted, based on the modified Swaziland MICS questionnaires, and used throughout the processing. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software programme, and syntax and tabulation plans developed for the global MICS4 were customized for this purpose.

Response rate

Of the 5,475 households selected for the sample nationally, 5,074 households were found to be occupied. Of these, 4,834 households were interviewed successfully yielding a household response rate of 95 percent. Among the interviewed households, 4,956 women age 15–49 years and 4,646 men age 15–59 years were identified. Of this number, 4,688 women and 4,179 men were successfully interviewed, yielding a response rate of 95 percent and 90 percent respectively. In addition, 2,711 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 2,647, corresponding to a response rate of 98 percent. Overall response rates of 90, 86 and 93 percent are calculated for under-five’s, women’s and men’s interviews respectively.

Responses varied slightly by residence with higher rates for women and men in rural areas than in urban areas. The situation was the reverse for children under-five where rural areas had higher response rates than urban areas. The overall response rate for women, men and children under five years in rural areas were, however, higher than in urban areas. The main reason for non-response among households and eligible individuals was the failure to find these individuals at home despite several visits to the households. Regional differentials also exist with all the regions having a 90 percent or higher response rate for all the questionnaires with the exception of Hhohho and Shiselweni regions that had 88 and 89 percent response rate, respectively, for the men’s questionnaire.

Sampling error estimates

The sample of respondents selected in the 2010 Kingdom of Eswatini MICS is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey results.

The following sampling error measures are presented in this appendix for each of the selected indicators:

Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). A standard error is the square root of the variance. The Taylor linearization method is used for the estimation of standard errors. Coefficient of variation (se/r) is the ratio of the standard error to the value of the indicator. Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling. The square root of the design effect, called the design factor (deft) is used to show the efficiency of the sample design. A deft value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a deft value above 1.0 indicates the increase in the standard error due to the use of a more complex sample design. Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall. For any given statistic calculated from the survey, the value of that statistics will fall within a range of plus or minus two times the standard error (p + 2.se or p – 2.se) of the statistic in 95 percent of all possible samples of identical size and design. For the calculation of sampling errors from the MICS data, the SPSS Complex Samples module has been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each

SZ：出生时性别比例：新生儿男女比例在12-01-2017达1.030Ratio，相较于12-01-2016的1.030Ratio保持不变。SZ：出生时性别比例：新生儿男女比例数据按年更新，12-01-1962至12-01-2017期间平均值为1.030Ratio，共21份观测结果。该数据的历史最高值出现于12-01-2017，达1.030Ratio，而历史最低值则出现于12-01-2017，为1.030Ratio。CEIC提供的SZ：出生时性别比例：新生儿男女比例数据处于定期更新的状态，数据来源于World Bank，数据归类于全球数据库的斯威士兰 – 表 SZ.世行.WDI：人口和城市化进程统计。

South Africa is expected to register the highest unemployment rate in Africa in 2024, with around ** percent of the country's labor force being unemployed. Djibouti and Eswatini followed, with unemployment reaching roughly ** percent and ** percent, respectively. On the other hand, the lowest unemployment rates in Africa were in Niger and Burundi. The continent’s average stood at roughly ***** percent in the same year. Large shares of youth among the unemployed Due to several educational, socio-demographic, and economic factors, the young population is more likely to face unemployment in most regions of the world. In 2024, the youth unemployment rate in Africa was projected at around ** percent. The situation was particularly critical in certain countries. In 2022, Djibouti recorded a youth unemployment rate of almost ** percent, the highest rate on the continent. South Africa followed, with around ** percent of the young labor force being unemployed. Wide disparities in female unemployment Women are another demographic group often facing high unemployment. In Africa, the female unemployment rate stood at roughly ***** percent in 2023, compared to *** percent among men. The average female unemployment on the continent was not particularly high. However, there were significant disparities among African countries. Djibouti and South Africa topped the ranking once again in 2022, with female unemployment rates of around ** percent and ** percent, respectively. In contrast, Niger, Burundi, and Chad were far below Africa’s average, as only roughly *** percent or lower of the women in the labor force were unemployed.